Nonlinear parabolic equation model for finite-amplitude sound propagation in an inhomogeneous medium over a nonflat, finite-impedance ground surface

Leissing, Thomas; Jean, Philippe; Defrance, Jérôme; Soize, Christian

doi:10.1121/1.2935953

Cited by 1 publication

(3 citation statements)

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“…In a previous work, the original NPE model has been extended to propagation within and over porous ground layers [24,25]. In this model the porous layer is assumed to be equivalent to a continuous fluid medium.…”

Section: General Overview Of Npe Modelsmentioning

confidence: 99%

“…The NPE model is well adapted for long-range sound propagation applications and it can account for most features of weakly non-linear sound propagation outdoors: geometrical spreading, weak non-linearities, refraction effects (see for example [27,6]), site topography [24], ground impedance [23] and thermoviscous effects [39]. Different models, such as the Fast Field Program (FFP, see [14,31]) or the (linear, frequency-domain) Parabolic Equation (PE, see [15]) could as well be used.…”

Section: Scope and Range Of Applicabilitymentioning

confidence: 99%

“…Once the parameters w opt 1 and w opt 2 are identified for u 1 and u 2 one can solve the stochastic equations (24) and (25) using the Monte Carlo method with these parameters and construct the associated confidence region as explained in section 8.3. Confidence regions are constructed with a probability level P c = 0.98 and with ν = 500 realisations of the stochastic model.…”

Section: Solution Of the Stochastic Propagation Model Construction Omentioning

confidence: 99%

See 2 more Smart Citations

Computational Model for Long-Range Non-Linear Propagation over Urban Cities

Leissing¹,

Soize²,

Jean³

et al. 2010

Acta Acustica united with Acustica

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A computational model for long-range non-linear sound propagation over urban environments is described. First the probability model of the geometrical parameters of an urban environment are determined using Information Theory and the Maximum Entropy Principle. The propagation model is then presented: it is based on the non-linear parabolic equation (NPE) and its extension to propagation in porous media, in which the urban layer of the real system is represented by a porous ground layer. The uncertainties introduced by the use of this simplified model and the presence of the variability of the real system are taken into account with a probabilistic model. Reference solutions are obtained thanks to the boundary element method (BEM); these experimental observations are then used to identify the parameters of the probability model. This inverse stochastic problem is solved using an evolutionary algorithm which involves both the mean-square method and the maximum likelihood method. Applications and model validation are then presented for two different urban environment morphologies. It is shown that the identification method provides an accurate and robust way for identifying the stochastic model parameters, independently of the variability of the real system. Constructed confidence regions are in good agreement with the numerical observations.

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Section: General Overview Of Npe Modelsmentioning

confidence: 99%